Abstract
In general, a database system will not operate properly if it exist some null values of attributes in the system. In this paper, we propose a new approach to estimate null values in relational database, which utilize other clustering algorithm to cluster data, and use fuzzy correlation and distance similarity to calculate the correlation of different attribute. For verifying our method, this paper utilize mean of absolute error rate (MAER) as evaluation criterion to compare with other methods; it is shown that our proposed method proves importance than the existing methods for estimating null values in relational database systems.
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The authors would like to thank the anonymous referees for providing very helpful comments and suggestions. Their insight and comments led to a better presentation of the ideas expressed in this paper.
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Cheng, CH., Wang, JW. A new approach for estimating null value in relational database. Soft Comput 10, 104–114 (2006). https://doi.org/10.1007/s00500-004-0430-3
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DOI: https://doi.org/10.1007/s00500-004-0430-3